Simplex optimization is one of the simplest algorithms available to train a neural network. Understanding how simplex optimization works, and how it compares to the more commonly used back-propagation ...

Catherine PORTE: Doctor of Physical Sciences - Emeritus University Professor - EA7341 – Laboratory of Molecular Chemistry and Chemical and Energy Process Engineering at the Conservatoire National des ...

Traditionally optimization of analytical methods has been conducted using a univariate method, varying each parameter one-by-one holding fixed the remaining. This means in many cases to reach only ...

% Initial Simplex: X = [x1, x2, x3] that x = (X(1),X(2)) in ObjFunc %TolX = 1e-4; % TolX: The termination tolerance for x. %TolFun = 1e-4; % TolFun: The termination tolerance for the function value.

In this repository, I discuss a method I developed to find optimal experimental designs when there is a random effect. 'Optimal' in this context means that a design will minimize effort while ...

This work presents a systematic approach to determining the significance of the individual factors affecting the analytical performance of in-situ film electrode (FE) for the determination of Zn(II), ...